A Hybrid Reliable Routing Algorithm Based on LQI and PRR in Industrial Wireless Networks

Link quality estimation plays a vital role in wireless sensor networks, which can improve transmission efficiency and reduce node energy consumption by selecting the links with good quality. Packet Reception Ratio (PRR), Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI) are typical metrics for link quality estimation. However, there is a lack of quantitative analysis on the convergence of these three metrics in existing studies. More specifically, what the size of time window should be used to process these metrics to reflect link quality more accurately? To solve this problem, this paper conducted comprehensive and quantitative analysis on the convergence of PRR, RSSI and LQI through collecting and analyzing large amounts of experimental data. Experimental results show that only about 10 packets are enough for RSSI and LQI to evaluate the link quality accurately, while 50 packets are needed for PRR under the same conditions.

This paper is concerned with a wireless receiving link evaluation method using statistical means of received signal strength indicator (RSSI) and link quality indicator (LQI) based on the IEEE 802.15.4 protocol for wireless sensor networks. Traditional methods using single RSSI and single LQI based on the IEEE 802.11 protocol have the disadvantage of the inaccurate evaluation. In this paper, we carry out a quantitative emulation experiment via computing statistical means of RSSI and LQI based on wireless sensor networks protocol of IEEE 802.15.4. Tested numerical values are analyzed using MATLAB and SPSS by defining the wireless link evaluation sensitivity. Result curves of RSSI to packet reception rate (PRR) and LQI to PRR we finally derive are shown that statistical means of RSSI and LQI can obtain the status information of receiving links more accurately, compared with the traditional wireless link evaluation using single RSSI and single LQI.

Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments.

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

We propose the use of a mutually complementary communication protocol (MCCP) for indoor sensor/actuator networks based on multi-interface communications. The MCCP uses several metrics which use packet reception ratio (PRR) against link quality indicator (LQI) in each interface to detect a better path for transmitting data. In this work, we used IEEE 802.15.4 wireless communications and power line communications (PLCs) for constructing the indoor sensor/actuator networks. To evaluate the performance of the MCCP, we developed evaluation boards which are connected with both IEEE 802.15.4 and the PLC module. Experimental results show that interface switching method using PRR against LQI is useful for routing part of the MCCP.

Due to an increasing number of sensors deployed in cars, recently there is a growing interest in implementing a wireless sensor network within a car. In this paper, we report the results of packet transmission experiments using ZigBee sensor nodes within a car under various scenarios. The results of the experiments suggest that both Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI) can only be used as a threshold-based indicator to evaluate the link quality - indicating poor link quality when dropping below a certain threshold. Preliminary experimental results show that a detection algorithm developed by the authors based on RSSI/LQI/error patterns and an adaptive strategy might increase the goodput performance of the link while improving power consumption of the radio.

With the success of wireless sensor networks (WSNs), traditional engineering and infrastructure industries are starting to develop solutions using WSN technologies. One of the main challenges of designing and developing WSNs for industrial monitoring and control is satisfying their strict reliability requirements. In this paper, we present a network-level reliability model, namely, end-to-end data delivery reliability (E2E-DDR), for estimating and optimizing the reliability performance of WSNs. In the E2E-DDR model, a framework is presented for capturing the mapping function between the packet reception ratio, background noise, and received signal strength (RSS). We use an alpha-stable distribution to accurately represent the background noise and a modified log-normal path loss model to more realistically describe the RSS. We also report a comprehensive performance evaluation performed by applying the E2E-DDR model in a real-world case study to estimate the network-level reliability and optimize the WSN deployment parameters. Note to Practitioners —The goal of this paper is to improve the estimation and optimization of the network-level reliability performance of industrial wireless sensor networks (WSNs) to satisfy their strict control requirements. In harsh industrial application scenarios, many factors affect radio link quality, such as RF transmit power, communication distance, and random background noise. Existing link quality estimation approaches mainly focus on providing a smoothed estimation of radio link quality without any solution for optimizing communication reliability to satisfy certain requirements. This paper suggests a new approach in which WSN nodes are used to measure and estimate the parameters of the scenario in which the nodes will be deployed and then to estimate and optimize the worst case reliability (which is a lower-bound value rather than a smoothed value) to ensure that the network is qualified. Through a real-world case study, we demonstrate how to estimate the lower bound on reliability and how to optimize the reliability by computing the maximum deployment distance between nodes as an example. The experiments suggest that this approach is feasible.

Packet losses, an important class of adverse events in wireless sensor networks, can be caused by either misbehaving nodes, or attacks focused on the wireless links. Understanding the underlying cause is critical for effective response measures to restore network functionality. Midi et al. (2015) proposed an approach for fine-grained analysis (FGA) of packet losses that profiles the wireless links between the nodes using resident metrics, such as the received signal strength indicator (RSSI) and the link quality indicator (LQI), to accurately diagnose the root causes of the losses. In our work, we design an approach that enhances such previous approach by leveraging a statistical model for determining optimal system thresholds based on the variances of RSSI and LQI, and also supporting individual per-link thresholds. Our validation through real sensor data shows that our model is accurate and leads to an optimal fine-grained analysis of the underlying causes of packet losses.

ETX (Expected Transmission Count) is a well-known link quality metric which has been widely used to improve the performance of ad-hoc routing protocols. However, ETX shows poor performance under high traffic load. To address this problem, this paper proposes a new link quality estimation metric called HETX (High load Expected Transmission Count) that takes into account the effects of routing control messages on the link quality under high traffic load. A reliable routing protocol using HETX is also proposed, which is called LQDV (Link Quality Distance Vector). Simulations are conducted to compare the performance of three metrics HETX, ETX and minimum hopcount. The simulation results show that HETX outperforms minimum hopcount and ETX in terms of throughput and delivery ratio under high load.

This paper presents a novel transmission power control protocol for body area networks. Conventional transmission power control protocols adjust the transmission power on the basis of the received signal strength indication (RSSI). However, in case of the presence of interference, the RSSI is not a correct indicator to determine the link state. We first present the empirical evidence for this and then propose a practical protocol to discriminate between the signal attenuation and interference using the RSSI and link quality indication (LQI). This protocol controls the transmission power and avoids interference based on the link state. Finally, we discuss the implementation of the proposed protocol on Tmote Sky and evaluate the performance in the presence and absence of interference. The experimental results showed that the proposed protocol has high energy-efficiency and reliability, even in the presence of interference.

WirelessHART is one of the most widely used technologies in industrial wireless networks. However, its performance is highly influenced by the quality of wireless channels. To improve the reliability of wireless communications, WirelessHART employs channel blacklisting and channel hopping mechanisms, which highlights the importance of channel assessment. Traditional methods generally resort to packet reception ratio (PRR) of the previous time slot to assess and allocate channels, but this is not accurate. In this paper, we propose a learning-based framework for predicting the PRR, and on the basis of the predicted PRR, we develop a heuristic channel selection algorithm to confirm the channel list, which takes into account the balance of channel diversity and route diversity. Simulation results demonstrate that our algorithm outperforms existing ones in terms of achieved reliability.

Link quality is important and can greatly affect the performance of wireless transmission algorithms and protocols. Currently, researchers have proposed a variety of approaches to implement link quality estimation. However, the estimated result of link quality is not accurate enough and the error is large, so they may lead to the failure of routing algorithm and protocol. In this paper, a novel method is proposed to achieve the more accurate estimation of link quality than before. This method employs Bernoulli sampling-based algorithm to complete the estimation of link quality. The problem is modeled as calculation of estimators based on Bernoulli sampling data. The authors further prove that the calculation results are accurate by probability theory. Furthermore, according to link quality estimation, the authors also provide a centralized routing algorithm and a distributed improvement algorithm in order to switch the data transmission on the better quality link. Finally, the extensive experiment results indicate that the proposed methods obtain high performance in terms of energy consumption and accuracy.

Routing protocol plays an important role in data communication. A wireless sensor network (WSN) is usually deployed in scenarios where efficient and energy-aware routing protocols are desired. In wireless sensors, the radio-frequency (RF) modules consume most of the energy. Routing metrics are important in determining paths and maintaining the quality of service in routing protocols. The most efficient metrics need to send packets to maintain link-quality measurement using the RF module. In this article, two prominent link-quality metrics-received signal strength indication (RSSI) and link-quality indication (LQI)-are introduced; the symmetry of RSSI and LQI in two directions has been studied, and relations between the expected transmission count (ETX), RSSI, and LQI as link-quality metrics have been analyzed. The evaluation in this article is based on a series of WSN test beds in real scenarios. The collected data from the test beds show symmetry in the RSSI in both directions as well as a significant correlation between the RSSI and distance, making RSSI a suitable link-quality metric for use in routing protocols for devices that work in limited-resources scenarios.

The accuracy and the reactivity of link quality estimators are key concepts in Mobile Ad hoc networks (MANETs) and especially in Vehicular Ad hoc Networks (VANETs), since routing process uses link quality related metrics based on neighbour information for making routing decisions. The Expected Transmission Count (ETX) is the most salient metric that assesses the link quality for wireless ad hoc and mesh networks. Its estimation varies according to the link changes like disruption and bidirectional to unidirectional switching. Such changes occur more often in highly mobile networks like VANETs. In order to be efficient routing protocols have to deal with these events. It has been observed that current implementation of ETX leads to a limited accuracy and cannot be efficient in VANETs. In this paper is presented an algorithm which makes the ETX metric more adapted for VANETs. Our contribution significantly improves the reactivity and the accuracy of the metric. In addition, our metric is not limited to the link quality estimation but also brings a link stability information. This results a new metric called Fast-ETX (F-ETX). This metric has been tested under realistic physical layer and mobility patterns to evaluate its reactivity, accuracy and stability properties.

A mobile ad hoc network (MANET) is a self-organizing network of mobile nodes which can form a dynamic topology. All the nodes generally have a limited transmission range and move freely throughout the network. So implementing a good routing protocol to react the link state changing is a critical issue in current research. From now on, a popular method is introducing a link quality evaluation (LQE) mechanism in routing algorithm. In this paper, we study the link quality evaluation scheme based on traffic-based metrics, such as packet reception ratio (PRR), and find two flaws (one is the assessment lagging and the other is the sample bias) which result in large handoff delay in routing protocols, especially when the PRR-like scheme is used in mobile environments. Therefore, we propose a link quality prediction (LQP) model to sense the link state by analyzing the Signal to Noise ratio of the neighbor link, and using grey theory to tackle the small sample size problem. Finally we set up mobile nodes test-bed to validate the scheme. Based on comparison of previous schemes, the LQP's performance is far better in handoff delay and packet loss rate.